Abstract

Abstract Algorithms have never been more influential, yet our collective understanding of how they transform massive networks of cultural power has not kept pace. This is especially true when it comes to economic algorithms, which operate as black boxes largely inaccessible to the majority of citizens whose worlds they continuously reshape. This essay offers a rhetorical approach to reading algorithms—not only to challenge the positivism and mathematical realism that naïvely apotheosizes algorithms and algorithmic culture but more importantly to become critical informants, scholars who can open up these black boxes for fellow citizens, examine the hidden assumptions therein, and study how they actively transform our social-material worlds. The essay’s exemplar is the 2008 financial crisis and a little-known algorithm called the Li Guassian copula, which played a major role in the spread of subprime mortgages. I argue that this copula puts on spectacular display the power of algorithms as principles of composition—actants that materially expand our social collectives even as they marginalize human agency and practical judgment with forms of technological rationality that, in the case of the Li copula, concentrated the networks of structured finance around a single decision apparatus, rendering those networks both larger and, contra conventional wisdom, more fragile.

Journal
Rhetoric & Public Affairs
Published
2019-12-01
DOI
10.14321/rhetpublaffa.22.4.0569
CompPile
Search in CompPile ↗
Open Access
Closed
Topics
Export

Citation Context

Cited by in this index (0)

No articles in this index cite this work.

References (102)

  1. 1. Financial Crisis Inquiry Commission, The Financial Crisis Inquiry Report: Final Report of the National Com…
  2. 2. Michael Lewis, The Big Short: Inside the Doomsday Machine (New York: W. W. Norton, 2010), 73.
  3. 3. Paul Krugman, The Return of Depression Economics and the Crisis of 2008 (New York: W. W. Norton, 2009), 155.
  4. 4. Gretchen Morgenson and Joshua Rosner, Reckles$ Endangerment: How Outsized Ambition, Greed, and Corruption …
  5. 5. Ed Finn, What Algorithms Want: Imagination in the Age of Computing (Cambridge, MA: MIT Press, 2017), 7. Wh…
Show all 102 →
  1. 6. On issues of algorithmic inaccessibility, see Finn, What Algorithms Want, especially chaps. 1 and 3.
  2. 7. I will develop the concept of the horizon of judgment in the body of the essay. In short, it refers to the…
  3. 8. This copula first emerged in David X. Li, “On Default Correlation: A Copula Function Approach,” August 15,…
  4. 9. For the original article on rhetoric and math, see Philip Davis and Reuben Hersh, “Rhetoric and Mathematic…
  5. 10. It is important to note here that while I take up Latour’s ideas about mathematical discourse as a provoc…
  6. 11. Neal Thomas, “Social Computing as a Platform for Memory,” Culture Machine (2013): 10.
  7. 12. As Bernard Steigler states concisely: “something absolutely new happens when the conditions of memorizati…
  8. 13. Frank Pasquale, The Black Box Society: The Secret Algorithms That Control Money and Information (Cambridg…
  9. 14. Pasquale and many other scholars see in the rise of an algorithmic culture the simultaneous and correlate…
  10. 15. For an excellent collection of relevant literature on these issues, see the Social Media Collective readi…
  11. 16. Cathy O’Neil, cited in Tom Upchurch, “To Work for Society, Data Scientists Need a Hippocratic Oath with T…
  12. 17. Pasquale, The Black Box Society, 4.
  13. 18. See Mittelstadt et al., “The Ethics of Algorithms,” 12–14.
  14. 19. Marc Lenglet espouses a widely shared view that “behind every algorithm lies a human,” and while I agree …
  15. 20. For more on these rapidly transforming learning algorithms, see O’Neil, Weapons of Math Destruction; Neil…
  16. 21. To clarify: plenty of research exists on the construction of algorithms from the technical fields of math…
  17. 22. Lenglet, “Algorithms and the Manufacture of Financial Reality,” 319. Even in Finn’s book, which has many …
  18. 23. Overemphasis on algorithmic implementation also tends to treat algorithms as finished products, thus rein…
  19. 24. For contemporary research along these lines, see Reyes, “Stranger Relations.”
  20. 25. Brian Rotman, Mathematics as Sign: Writing, Imagining, Counting (Stanford, CA: Stanford University Press,…
  21. 26. A fuller explication of a constitutive approach to mathematical discourse can be found in Rotman’s work […
  22. 27. See Reyes, “The Rhetoric in Mathematics”; and George Lakoff and Rafael Núñez, Where Mathematics Comes Fro…
  23. 28. There are a few scholars that buck this trend, challenging the human-centric approach to algorithms (see …
  24. 29. In short, the risk in focusing on the construction of algorithms is that we, as critical scholars, lose s…
  25. 30. Plutarch, Marcellus’ Life, trans. Bernadotte Perrin (Cambridge, MA: Harvard University Press, 1967–1975),…
  26. 31. Plutarch, Marcellus’ Life, xiv, 7–9.
  27. 32. Plutarch, Marcellus’ Life, xiv, 7–9.
  28. 33. Plutarch, Marcellus’ Life, xiv, 7–9.
  29. 34. Bertrand Russell, “The Study of Mathematics,” New Quarterly 1 (1907): 30–42.
  30. 35. For economy’s sake, I dare not go too far into the woods on this point. Suffice it to say that whole book…
  31. 36. Martha Nussbaum shows how geometry emerged for thinkers like Parmenides and Plato as an alternative to do…
  32. 37. Bruno Latour, We Have Never Been Modern (Cambridge, MA: Harvard University Press, 1993), 110.
  33. 38. Latour, We Have Never Been Modern, 110.
  34. 39. Barad, Meeting the Universe Halfway, 71–94.
  35. 40. Latour’s position here is consistent with his broader philosophical rejection of modernist metaphysics, w…
  36. 41. Latour, We Have Never Been Modern, 129.
  37. 42. Latour, Science in Action, 244.
  38. 43. European exploration of the East Pacific in the eighteenth century offers one last example to underscore …
  39. 44. The question of what becomes of rhetoric through a Latourian approach would require a whole other essay t…
  40. 45. Felix Salmon, “The Formula That Killed Wall Street,” Significance (February 2012): 16.
  41. 46. Sam Jones, “The Formula That Felled Wall St,” Financial Times, April 24, 2009, https://www.ft.com/content…
  42. 47. Alan Greenspan, October 12, 2005, cited in Paul Krugman, End This Depression Now (New York: W. W. Norton,…
  43. 48. Salmon, “The Formula,” 19.
  44. 49. As will be discussed in the analysis, the discursive shift from “model” and “forecasting” to “technology”…
  45. 50. For more on the impact of MBSs on the rise of neoliberalism and the transformation of the home into an “a…
  46. 51. The risk exposure changes because investors in MBSs are paid out hierarchically. For example, AAA investo…
  47. 52. Hanan, Ghosh, and Brooks’s “Banking on the Present” offers an excellent overview of the rise of MBSs with…
  48. 53. The basic mathematics behind default correlation are as follows: correlation is considered a probability …
  49. 54. Coval, Jurek, and Stafford, “The Economics of Structured Finance,” 16.
  50. 55. As Coval, Jurek, and Stafford note, the use of the Li copula to “repackage risks and to create ‘safe’ ass…
  51. 56. Human judgment has long been associated with the ability to take in particular information from one’s con…
  52. 57. Li, “On Default Correlation,” 2.
  53. 58. A basic tenant of realism is that to have unmediated access to "the real" one must cast off all ideology …
  54. and Donald N. McCloskey, "Two Replies and a Dialogue on the Rhetoric of Economics: Maki, Rappaport, and Rosen…
  55. 59. Aune, Selling the Free Market, 40; see also Hanan, Ghosh, and Brooks, “Banking on the Present.”
  56. 60. Li, “On Default Correlation,” 2.
  57. 61. While the mathematization of economics first began with the rise of probability and statistics in the 194…
  58. 62. Li, “On Default Correlation,” 2.
  59. 63. Li, “On Default Correlation,” 3.
  60. 64. For extensive discussion of scalable versus nonscalable phenomena, see Nassim Taleb, The Black Swan: The …
  61. 65. Federal Reserve Bank of Saint Louis, “Delinquency Rate on Single-Family Residential Mortgages, Booked In …
  62. 66. Some of these elements of his argument are explicit in Li’s text (like the collective poor understanding …
  63. 67. Note that for the purposes of this analysis, we will treat “function,” “equation,” and “algorithm” as syn…
  64. 68. Li, “On Default Correlation,” 3–4.
  65. 69. Latour, Science in Action, 244.
  66. 70. See Theodore M. Porter, Trust in Numbers: The Pursuit of Objectivity in Science and Public Life (Princeto…
  67. 71. Li, “On Default Correlation,” 6–8.
  68. 72. Li, “On Default Correlation,” 7.
  69. 73. Li, “On Default Correlation,” 16.
  70. 74. Li, “On Default Correlation,” 16.
  71. 75. By terraforming I mean the ways math can transform our social-material worlds.
  72. 76. Latour, We Have Never Been Modern, 129.
  73. 77. Finn, What Algorithms Want, 20.
  74. 78. On wayfinding and the parahippocampus, see Neil Burgess, Eleanor A. Maguire, and John O'Keefe, "The Human…
  75. and Betsy Sparrow, Jenny Liu, and Daniel M. Wegner, "Google Effects on Memory: Cognitive Consequences of Havi…
  76. and Alexis C. Madrigal, "How Netflix Reverse Engineered Hollywood," Atlantic, January 2, 2014, http://theantl…
  77. 79. See Coval, Jurek, and Stafford, “The Economics of Structured Finance”; and Lewis, The Big Short.
  78. 80. The Li copula sponsored many other hybrids within the CDO market, such as cash, synthetic, and hybrid CDO…
  79. 81. McLean and Nocera, All the Devils Are Here, 123.
  80. 82. For a more in-depth explanation of pooling and tranching, see Coval, Jurek, and Stafford, “The Economics …
  81. 83. Coval, Jurek, and Stafford, “The Economics of Structured Finance,” 8-9.
  82. 84. By way of example, take the junior tranche in our hypothetical loan pool and imagine combining it with ot…
  83. 85. The Financial Crisis Inquiry Report, 130; and McLean and Nocera, All the Devils Are Here, 201.
  84. 86. McLean and Nocera, All the Devils Are Here, 123; Efraim Benmelech and Jennifer Dlugosz, “The Credit Ratin…
  85. 87. Lewis, The Big Short, 73.
  86. 88. Coval, Jurek, and Stafford, “The Economics of Structured Finance,” 8-12.
  87. 89. Taleb, The Black Swan, xxix. For more on Gaussian model fragility, see Espen Gaarder Haug and Nassim Nich…
  88. 90. Taleb, The Black Swan, 239.
  89. 91. I borrow the term “sliced” from Barad, who uses it to describe the power of new knowledge as the power to…
  90. 92. Finn, What Algorithms Want, 49.
  91. 93. There are many ways in which numbers can influence one’s perception: the simplest example emerges from an…
  92. 94. On anchoring within disjunctive systems, see Amos Tversky and Daniel Kahneman, “Judgment Under Uncertaint…
  93. 95. Tversky and Kahneman, “Judgment Under Uncertainty,” 428.
  94. 96. Anchoring is only one dimension of the copula’s agential force, and it would not have had the impact it d…
  95. 97. Stormer, “Rhetoric’s Diverse Materiality,” 306.
  96. 98. This approach is both pragmatic and philosophically disinclined to adoption of a single method, for the p…
  97. 99. Torin Monahan, “Editorial: Algorithmic Fetishism,” Surveillance and Society 16 (2018): 1.